*SEM 2019

The Eighth Joint Conference on Lexical and Computational Semantics

June 6-7, 2019, Minneapolis, USA

Co-located with NAACL 2019


We are pleased to announce that SIGLEX and SIGSEM, special interest groups of the ACL, are organizing the 8th Joint Conference on Lexical and Computational Semantics: *SEM. *SEM 2019 will be co-located with NAACL-HLT 2019 in Minneapolis (USA), and it will take place on the 6-7 of June 2019. We will update this website with more information as it becomes available.

Latest news

April 09, 2019 If you need a visa invitation letter, please fill the form here. Visit this link to find more information on the US visa application process.

March 05, 2019 The long and short paper submission deadline has been extended. New deadline: March 10, 2019. See Important Dates section on the home page.

December 29, 2018. The deadlines for long & short paper submissions, notification of acceptance, and camera ready versions are now posted. See Important Dates section on the home page.


Accepted Papers

Composition of Embeddings : Lessons from Statistical Relational Learning Damien Sileo, Tim Van de Cruys, Camille Pradel and Philippe Muller
HELP: A Dataset for Identifying Shortcomings of Neural Models in Monotonicity Reasoning Hitomi Yanaka, Koji Mineshima, Daisuke Bekki, Kentaro Inui, Satoshi Sekine, Lasha Abzianidze and Johan Bos
Second-order contexts from lexical substitutes for few-shot learning of word representations Qianchu Liu, Diana McCarthy and Anna Korhonen
Automatic Accuracy Prediction for AMR Parsing Juri Opitz and Anette Frank
An Argument-Marker Model for Syntax-Agnostic Proto-Role Labeling Juri Opitz and Anette Frank
Generating Animations from Screenplays Yeyao Zhang, Eleftheria Tsipidi, Sasha Schriber, Mubbasir Kapadia, Markus Gross and Ashutosh Modi
Pre-trained Contextualized Character Embeddings Lead to Major Improvements in Time Normalization: a Detailed Analysis Dongfang Xu, Egoitz Laparra and Steven Bethard
Bot2Vec: Learning Representations of Chatbots Jonathan Herzig, Tommy Sandbank, Michal Shmueli-Scheuer and David Konopnicki
Are We Consistently Biased? Multidimensional Analysis of Biases in Distributional Word Vectors Anne Lauscher and Goran Glavaš
On Adversarial Removal of Hypothesis-only Bias in Natural Language Inference Yonatan Belinkov, Adam Poliak, Stuart Shieber, Benjamin Van Durme and Alexander Rush
Word Embeddings (Also) Encode Human Personality Stereotypes Oshin Agarwal, Funda Durupınar, Norman I. Badler and Ani Nenkova
A Semantic Cover Approach for Topic Modeling Rajagopal Venkatesaramani, Doug Downey, Bradley Malin and Yevgeniy Vorobeychik
SURel: A Gold Standard for Incorporating Meaning Shifts into Term Extraction Anna Hätty, Dominik Schlechtweg and Sabine Schulte im Walde
MCScript2.0: A Machine Comprehension Corpus Focused on Script Events and Participants Simon Ostermann, Michael Roth and Manfred Pinkal
Deconstructing multimodality: visual properties and visual context in human semantic processing Christopher Davis, Luana Bulat, Anita Lilla Verő and Ekaterina Shutova
Learning Graph Embeddings from WordNet-based Similarity Measures Andrey Kutuzov, Mohammad Dorgham, Oleksiy Oliynyk, Chris Biemann and Alexander Panchenko
Bayesian Inference Semantics: A Modelling System and A Test Suite Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin and Aleksandre Maskharashvili
Neural User Factor Adaptation for Text Classification: Learning to Generalize Across Author Demographics Xiaolei Huang and Michael J. Paul
Incivility Detection in Online Comments Farig Sadeque, Stephen Rains, Yotam Shmargad, Kate Kenski, Kevin Coe and Steven Bethard
Abstract Graphs and Abstract Paths for Knowledge Graph Completion Vivi Nastase and Bhushan Kotnis
Word Usage Similarity Estimation with Sentence Representations and Automatic Substitutes Aina Garí Soler, Marianna Apidianaki and Alexandre Allauzen
Beyond Context: A New Perspective for Word Embeddings Yichu Zhou and Vivek Srikumar
A Corpus of Negations and their Underlying Positive Interpretations Zahra Sarabi, Erin Killian, Eduardo Blanco and Alexis Palmer
Enthymemetic Conditionals Eimear Maguire
Acquiring Structured Temporal Representation via Crowdsourcing: A Feasibility Study Yuchen Zhang and Nianwen Xue
Exploration of Noise Strategies in Semi-supervised Named Entity Classification Pooja Lakshmi Narayan, Ajay Nagesh and Mihai Surdeanu
Improving Generalization in Coreference Resolution via Adversarial Training Sanjay Subramanian and Dan Roth
Probing What Different NLP Tasks Teach Machines about Function Word Comprehension Najoung Kim, Roma Patel, Adam Poliak, Patrick Xia, Alex Wang, Tom McCoy, Ian Tenney, Alexis Ross, Tal Linzen, Benjamin Van Durme, Samuel R. Bowman and Ellie Pavlick
Multi-Label Transfer Learning for Multi-Relational Semantic Similarity Li Zhang, Steven Wilson and Rada Mihalcea
Scalable Cross-Lingual Transfer of Neural Sentence Embeddings Hanan Aldarmaki and Mona Diab
Improving Human Needs Categorization of Events with Semantic Classification Haibo Ding, Ellen Riloff and Zhe Feng
Target Based Speech Act Classification in Political Campaign Text Shivashankar Subramanian, Trevor Cohn and Timothy Baldwin

Keynote Speakers

The following speakers have accepted to give keynotes at *SEM 2019.

Speaker: Ellen Riloff

Date: TBC

Title: Identifying Affective Events and the Reasons for their Polarity

Abstract: Recognizing affective states is essential for narrative text understanding and for applications such as conversational dialogue, summarization, and sarcasm recognition. Many tools have been developed to recognize explicit expressions of sentiment, but affective states can also be inferred from events. This talk will focus on "affective events", which are generally desirable or undesirable experiences that implicitly suggest an affective state for the experiencer. For example, buying a home is usually desirable and associated with a positive affective state, but being laid off is undesirable and associated with a negative state. First, we will describe a weakly supervised learning method to induce affective events from a text corpus by optimizing for semantic consistency. Second, we aim to characterize affective events based on Human Needs Categories, which often explain people's motivations, goals, and desires. We will present a co-training model for Human Needs categorization that uses an event expression classifier and an event context classifier to learn from both labeled and unlabeled texts.

Bio: Ellen Riloff is a Professor in the School of Computing at the University of Utah. Her primary research area is natural language processing, with an emphasis on information extraction, affective text analysis, semantic class induction, and bootstrapping methods that learn from unannotated texts. Prof. Riloff has served as the General Chair for the EMNLP 2018 conference, Program Co-Chair for the NAACL HLT 2012 and CoNLL 2004 conferences, on the NAACL Executive Board for 2004-2005 and 2017-2018, the Computational Linguistics Editorial Board, and the Transactions of the Association for Computational Linguistics (TACL) Editorial Board. In 2018, Prof. Riloff was named a Fellow of the Association for Computational Linguistics (ACL).

Speaker: Sam Bowman

Date: TBC

Title: Task-Independent Sentence Understanding

Abstract: This talk deals with the goal of task-independent language understanding: building machine learning models that can learn to do most of the hard work of language understanding before they see a single example of the language understanding task they're meant to solve, in service of making the best of modern NLP systems both better and more data-efficient. I'll survey the (dramatic!) progress that the NLP research community has made toward this goal in the last year. In particular, I'll dwell on GLUE—an open-ended shared task competition that measures progress toward this goal for sentence understanding tasks—and I'll preview a few recent and forthcoming analysis papers that attempt to offer a bit of perspective on this recent progress.

Bio: I have been on the faculty at NYU since 2016, when I finished my PhD with Chris Manning and Chris Potts at Stanford. At NYU, I'm a core member of the new school-level Data Science unit, which focuses on machine learning, and a co-PI of the CILVR machine learning lab. My research focuses on data, evaluation techniques, and modeling techniques for sentence understanding in natural language processing, and on applications of machine learning to scientific questions in linguistic syntax and semantics. I am an area chair for *SEM 2018, ICLR 2019, and NAACL 2019; I organized a twenty-three person team at JSALT 2018; and I earned a 2015 EMNLP Best Resource Paper Award and a 2017 Google Faculty Research Award.

Call for papers

*SEM 2019 brings together researchers interested in the semantics of natural languages and its computational modeling. The conference embraces symbolic and probabilistic approaches, and everything in between; theoretical contributions as well as practical applications are welcome. The long-term goal of *SEM is to provide a stable forum for the growing number of NLP researchers working on all aspects of semantics. Topics of interest include, but are not limited to:

  • Lexical semantics and word representations
  • Compositional semantics and sentence representations
  • Statistical, machine learning and deep learning methods in semantic tasks
  • Multilingual and cross-lingual semantics
  • Word sense disambiguation and induction
  • Semantic parsing; syntax-semantics interface
  • Frame semantics and semantic role labeling
  • Textual inference, entailment and question answering
  • Formal approaches to semantics
  • Extraction of events and causal and temporal relations
  • Entity linking; pronouns and coreference
  • Discourse, pragmatics and dialogue
  • Machine reading
  • Extra-propositional aspects of meaning
  • Multiword and idiomatic expressions
  • Metaphor, irony, and humour
  • Knowledge mining and acquisition
  • Common sense reasoning
  • Language generation
  • Semantics in NLP applications: sentiment analysis, abusive language detection, summarization, fact checking, etc.
  • Multidisciplinary research on semantics
  • Grounding and multimodal semantics
  • Human semantic processing
  • Semantic annotation, evaluation and resources
  • Ethical aspects and bias in semantic representations

Important Dates

Paper submission deadline: March 10, 2019
Notification of acceptance: April 3, 2019
Camera-ready papers due: April 10, 2019
Timezone: as long as it’s the date mentioned, anywhere on earth; UTC-12.

Submission Instructions

Submissions to *SEM 2019 must describe unpublished work and be written in English. We solicit both long and short papers.

Long papers describe original research and may consist of up to eight (8) pages of content, plus unlimited pages for references. Final versions of long papers will be given one additional page of content (up to 9 pages) so that reviewers' comments can be taken into account.

Short papers describe original focused research, project or system description, and may consist of up to four (4) pages, plus unlimited pages for references. Upon acceptance, short papers will be given five (5) content pages in the proceedings. Authors are encouraged to use this additional page to address reviewers comments in their final versions.

As the reviewing will be blind, the paper must not include the authors' names and affiliations. Furthermore, self-references that reveal the author's identity, e.g., "We previously showed (Smith, 1991) ..." must be avoided. Instead, use citations such as "Smith previously showed (Smith, 1991) ...". As for online paper sharing, at *SEM, we adopt the ACL policy for submission, which can be found here. Papers that do not conform to requirements will be rejected without review. For a paper to be included in the conference proceedings, at least one of the authors must be registered as a participant at the *SEM conference.

Submissions to *SEM should follow this year's NAACL style, as detailed here: https://naacl2019.org/calls/papers/

Please note that double submission of papers will need to be notified at submission.

Key dates

Paper submission deadline: March 10, 2019
Notification of acceptance: April 3, 2019
Camera-ready papers due: April 10, 2019
*SEM conference: June 6-7, 2019

Timezone: as long as it’s the date mentioned, anywhere on earth; UTC-12.

Organizing Committee

General Chair: Rada Mihalcea, University of Michigan, Ann Arbor
Program Chairs:

Ekaterina Shutova, University of Amsterdam

Lun-Wei Ku, Academia Sinica, Taiwan

Publications Chair: Kilian Evang, University of Düsseldorf
Publicity Chair: Soujanya Poria, NTU, Singapore

Area Chairs

Lexical semantics and word representations:

Anna Feldman, Montclair State University

Fabio Massimo Zanzotto, University of Rome Tor Vergata

Semantic composition and sentence representations:

Helen Yannakoudakis, University of Cambridge

Douwe Kiela, Facebook AI Research

Discourse, dialogue and generation :

Lea Frermann, Amazon Core AI

Lu Wang, Northeastern University

Machine learning for semantic tasks:

Roi Reichart, Technion - Israel Institute of Technology

Wilker Aziz, University of Amsterdam

Multidisciplinary & COI: Preslav Nakov, QCRI
Multilinguality: Marianna Apidianaki, CNRS
Human semantic processing / Psycholinguistics: Barry Devereux, Queen’s University Belfast
Semantics in NLP applications:

Dan Goldwasser, Purdue University

Saif Mohammad, National Research Council of Canada

Marek Rei, University of Cambridge

Resources and evaluation: Beata Beigman Klebanov, Educational Testing Service
Theoretical and formal semantics: Mehrnoosh Sadrzadeh, Queen Mary University of London

Contact us

Contact email: starsem2019.program.chairs@gmail.com

Website issues: Devamanyu Hazarika, NUS, Singapore

Twitter: https://twitter.com/_starsem